{"as_of":"2026-08-18T07:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b0f68d94d5e9c83f56dbc343bbb6057ab7dc4c5e38eba50495a5abd52f19cdc8","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T23:17:16.416370Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-15T23:17:16.574624Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2207.11649","last_updated":"2022-07-26T04:09:22Z","snapshot_observed_at":"2026-08-18T04:58:34.518382Z","submitted_at":"2022-07-24T03:34:21Z","title":"OCTAL: Graph Representation Learning for LTL Model Checking","version":2},"cited_work":{"arxiv_id":"2207.11649","doi":null,"metadata_source":"pith","pith_arxiv_id":"2207.11649","snapshot_observed_at":"2026-08-15T23:17:16.574624Z","title":"OCTAL: Graph Representation Learning for LTL Model Checking","venue":"cs.PL","work_id":"e11d8d6d-b8ab-470a-9cbc-ae0aaa39e050","year":2022},"citing_paper":{"arxiv_id":"2505.05106","last_updated":"2025-05-08T10:10:00Z","snapshot_observed_at":"2026-08-15T23:10:31.223875Z","submitted_at":"2025-05-08T10:10:00Z","title":"A Neuro-Symbolic Framework for Sequence Classification with Relational and Temporal Knowledge","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-15T23:17:16.416370Z"},"links":{"cited_paper":"/paper/2207.11649","citing_paper":"/paper/2505.05106"},"observation_digest":"sha256:d2b7e096d0a8f6003d0190a34215bdd303d7f93e89c8fec97131e28148016988","observation_id":"bb916b00-3778-4573-84c1-3dfb7af79fc7","resolution":{"observed_at":"2026-08-15T23:17:16.582833Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2207.11649/citation-record","integrity":"/paper/2207.11649/integrity","json":"/paper/2207.11649/citation-record.json","paper":"/paper/2207.11649"},"outbound":[],"paper":{"arxiv_id":"2207.11649","last_updated":"2022-07-26T04:09:22Z","latest_version":2,"primary_category":"cs.PL","snapshot_observed_at":"2026-08-18T04:58:34.518382Z","submitted_at":"2022-07-24T03:34:21Z","title":"OCTAL: Graph Representation Learning for LTL Model Checking"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2207.11649."}